Literature DB >> 24110204

A quantitative technique for assessing the change in severity over time in psoriatic lesions using computer aided image analysis.

Juan Lu, Ed Kazmierczak, Jonathan H Manton, Rodney Sinclair.   

Abstract

Psoriasis is a chronic skin disease affecting an estimated 125 million people worldwide. One of the key problems in the management of this condition is the objective measurement of lesion severity over time. Currently, severity is scored by clinicians using visual protocols leading to intra and inter observer variability that makes measurement of treatment efficacy subjective. In this paper, an automatic computer aided image analysis system is proposed that quantitatively assess the changes of erythema and scaling severity of psoriatic lesions in long-term treatment. The algorithm proposed in this paper works on 2D digital images by selecting features that can be used to accurately segment erythema and scaling in psoriasis lesions and assess their changes in severity, according to the popular psoriasis area and severity index (PASI). The algorithms are validated by developing linear models that correlate well with changes in severity scores given by dermatologists. To the best of our knowledge, no such computer assisted method for psoriasis severity assessment in a long-term treatment exists.

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Mesh:

Year:  2013        PMID: 24110204     DOI: 10.1109/EMBC.2013.6610017

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Design of an Algorithm for Automated, Computer-Guided PASI Measurements by Digital Image Analysis.

Authors:  Christine Fink; Tobias Fuchs; Alexander Enk; Holger A Haenssle
Journal:  J Med Syst       Date:  2018-11-03       Impact factor: 4.460

2.  Objective measurement of erythema in psoriasis using digital color photography with color calibration.

Authors:  A Raina; R Hennessy; M Rains; J Allred; J M Hirshburg; D G Diven; M K Markey
Journal:  Skin Res Technol       Date:  2015-10-30       Impact factor: 2.365

3.  Image-based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks.

Authors:  M J Schaap; N J Cardozo; A Patel; E M G J de Jong; B van Ginneken; M M B Seyger
Journal:  J Eur Acad Dermatol Venereol       Date:  2021-10-18       Impact factor: 9.228

  3 in total

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